Company field note
Auto-discovered from public company career pages; Aspirova links out to the original source.
Open opportunities
40 opportunities
This role sits in Research Operations and works closely with partnerships, research, hardware, and infrastructure. Partnerships sets the terms of each engagement and research owns the technical goal.
The Environment team supports research and production operations at Physical Intelligence. The team builds and maintains physical work spaces and keeps them supplied so work runs on schedule across every shift.
The Learning & Development Lead owns training and readiness for Physical Intelligence's robot operator workforce.
Physical Intelligence is bringing general-purpose AI into the physical world.
As a full stack Recruiter, you will help build the team that builds the robots - owning high-impact searches across research and engineering.
The Set Team plans, builds, and maintains these environments so research can run on real-world tasks.
As a Fullstack Software Engineer, you will build internal products that help Pi's research and operations teams move faster.
As an API Product Engineer, you'll build the product surface that allows other companies to use Pi's models much like developers use an LLM API today: bring their own data, fine-tune models, evaluate them, and run…
This role is a hands-on owner for a portfolio of annotation programs: partnering with researchers to understand what data they need and why, translating that into concrete requirements and rubrics, and running the…
As Pi's Operations Recruiter, you'll own the recruiting funnel from candidate generation through screening: creating enough qualified candidate flow, conducting initial screens, deciding who advances, and handing strong…
As a Software Engineer focused on AI productivity, you will build and roll out the tools that help us use AI effectively across the company.
The ML Infrastructure team supports and accelerates PI's core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast.
Training robot foundation models takes enormous amounts of multimodal data, much of it collected by third-party vendors and partners around the world.
